Live Online Data and Analytics for AML / CFT & Financial Crime Analytics Training Course
Live online, instructor-led · next cohort Nov 2, 2026 · from USD 800
Criminals move money faster than manual reviews can follow, and supervisors now expect institutions to prove that their monitoring finds real risk rather than flooding analysts with false alarms. Five days equip compliance teams to use data as their main detection tool. You work through customer and transaction datasets, build typologies for structuring, layering, trade-based laundering and terrorist financing, and write rule-based scenarios with thresholds you can defend. Sessions on alert tuning cover below-the-line testing, precision and recall, and segmentation of customers by risk. You also see how entity resolution, link analysis and graph methods expose hidden relationships between accounts, companies and beneficial owners.
The later sessions move from detection to action: triaging alerts, documenting investigations, drafting suspicious transaction reports and measuring programme performance with dashboards and management information. Machine learning for anomaly detection is introduced with attention to explainability, model governance and data quality. The programme suits AML and CFT compliance officers, money laundering reporting officers, financial intelligence unit analysts, internal auditors, fraud investigators and risk staff in banks, insurers, mobile money operators and regulators. Delivery is by classroom, online or in-house, with a CPD-accredited certificate.
At a Glance
How Live Online Training Works
Live online training, led by a trainer in real time, for participants anywhere.
More about live online training →- Format
- Live online, instructor-led
- Duration
- Mon - Fri (5 Days)
- Fee
- USD 800 (KES 80,000)
- Next start dates
- Nov 2, 2026, Nov 30, 2026, Dec 28, 2026
- Certificate
- Certificate of Completion
- What you need
- A computer with a reliable internet connection, a webcam and a headset
About this course
Financial institutions in Africa and beyond face growing expectations from regulators, correspondent banks and the Financial Action Task Force that their anti-money laundering and counter-terrorist financing controls are risk-based and evidenced with data. Legacy monitoring systems often generate thousands of low-value alerts, hide genuine red flags and leave compliance teams unable to explain why a rule exists or whether it works.
Over five days, participants learn how to prepare and profile transaction, customer and screening data, translate typologies into scenarios, and measure and tune detection performance. The programme covers customer risk segmentation, threshold setting, sampling and validation, network and link analysis, and the careful use of machine learning for anomaly detection. It then follows an alert through triage, investigation, case documentation and reporting to the financial intelligence unit, and closes with management information and governance of the analytics function.
The teaching is led by practitioners and built on anonymised datasets that participants query and visualise themselves. Short briefings introduce each method, after which small groups apply it to a realistic case. Participants finish with a tested monitoring scenario, an alert-tuning plan and a reporting dashboard design that can be adapted to their own institution.
Training Objectives
By the end of the programme, participants will be able to:
- Translate money laundering, terrorist financing and fraud typologies into measurable data-driven red flags.
- Prepare and profile transaction and customer data so that monitoring results can be trusted.
- Design, calibrate and document rule-based monitoring scenarios and thresholds.
- Evaluate alert quality using false-positive rates, below-the-line testing and sampling.
- Apply link and network analysis to identify related parties and beneficial ownership chains.
- Assess where machine learning adds value in detection and what governance it requires.
- Investigate alerts and draft clear suspicious transaction reports.
- Build dashboards that report monitoring performance to senior management and supervisors.
What you'll learn
Key Takeaways
Participants leave with:
- A tested transaction monitoring scenario with documented logic, thresholds and rationale.
- An alert-tuning method they can repeat on their own institution's data.
- A typology-to-red-flag library covering common laundering and financing patterns.
- A template for investigation notes and suspicious transaction report narratives.
- A draft management information dashboard for the board and compliance committee.
- A prioritised plan for improving data quality and analytics in their compliance function.
Training Methodology
Delivery relies on hands-on analysis rather than slides. The programme includes:
- Short practitioner briefings introducing each detection method
- Labs in Excel, SQL and Python on anonymised transaction datasets
- Small-group investigations of realistic financial crime cases
- Review of participants' own monitoring challenges in facilitated clinics
- A closing presentation of a scenario and dashboard design
Day 1: Financial Crime Risk and the Data Landscape
- Money laundering, terrorist financing and proliferation financing typologies
- Risk-based approach and the role of data in each control
- Sources: core banking, mobile money, KYC, screening and trade data
- Data quality, lineage and completeness issues in compliance data
- Profiling datasets with Excel and SQL
- Exercise: mapping typologies to available data fields
Day 2: Designing Monitoring Scenarios and Red Flags
- Rule logic: velocity, structuring, round amounts and dormant account reactivation
- Customer and product risk segmentation
- Setting thresholds with peer groups and statistical baselines
- Cash intensive business and cross-border payment scenarios
- Documenting scenario design for regulators and auditors
- Lab: building three scenarios in SQL
Day 3: Tuning, Testing and Validating Detection
- Alert volumes, false positives and analyst capacity
- Below-the-line and above-the-line testing
- Precision, recall and sampling approaches
- Back-testing scenarios on historical cases
- Change control for rules and model governance
- Lab: tuning a threshold and measuring the effect
Day 4: Network, Link and Anomaly Analysis
- Entity resolution and matching of customers, companies and addresses
- Link analysis for mule accounts and nominee structures
- Introduction to graph analytics and visualisation tools
- Anomaly detection with clustering and outlier methods in Python
- Explainability and bias in machine learning for compliance
- Case file: tracing a layering network
Day 5: Investigation, Reporting and Programme Performance
- Alert triage and case management workflow
- Writing investigation notes and suspicious transaction report narratives
- Feedback loops from reports to scenario improvement
- Key risk and performance indicators for the monitoring programme
- Dashboard design for senior management and the board
- Action plan for an analytics improvement project
The programme is aimed at professionals who detect, investigate or oversee financial crime risk, including:
- AML and CFT compliance officers
- Money laundering reporting officers and their deputies
- Financial intelligence unit and law enforcement analysts
- Transaction monitoring and sanctions screening analysts
- Internal and external auditors reviewing compliance programmes
- Fraud and forensic investigators
- Risk managers in banks, insurers and mobile money providers
- Supervisors and regulators of financial institutions
- Data analysts supporting compliance teams
Participants who attend the sessions and complete the practical labs are awarded a CPD-accredited Certificate of Completion from Vision Reach Global Consultancy.
Choose Where You Want to Learn
Data and Analytics for AML / CFT & Financial Crime Analytics Training Course Venues
KenyaNairobiNext Nov 9· 13 dates$1,500- KenyaMombasaNext Oct 26· 13 dates$1,600
- KenyaNaivashaNext Nov 2· 13 dates$1,500
- KenyaKisumuNext Oct 26· 13 dates$1,500
- KenyaMachakosNext Nov 2· 13 dates$1,600
UgandaKampalaNext Nov 2· 13 dates$1,900
RwandaKigaliNext Oct 26· 13 dates$1,900
TanzaniaArushaNext Nov 9· 13 dates$1,900- TanzaniaDodomaNext Oct 26· 13 dates$1,800
- TanzaniaDar es SalaamNext Oct 26· 13 dates$2,000
- TanzaniaZanzibarNext Nov 16· 13 dates$2,600
NigeriaLagosNext Nov 16· 13 dates$2,800- NigeriaAbujaNext Nov 9· 13 dates$2,800
South AfricaPretoriaNext Nov 2· 13 dates$3,200- South AfricaJohannesburgNext Nov 2· 13 dates$3,400
- South AfricaCape TownNext Oct 26· 13 dates$3,800
UAEDubaiNext Oct 26· 13 dates$3,800
GhanaAccraNext Nov 16· 13 dates$4,500
Scroll sideways to see all 18 cities →
Frequently Asked Questions About Live Online Data and Analytics for AML / CFT & Financial Crime Analytics Training Course
Everything you need to know about this course before you register.
By the end of the Data and Analytics for AML / CFT & Financial Crime Analytics programme, you'll be able to translate money laundering, terrorist financing and fraud typologies into measurable data-driven red flags, prepare and profile transaction and customer data so that monitoring results can be trusted, design, calibrate and document rule-based monitoring scenarios and thresholds, and evaluate alert quality using false-positive rates, below-the-line testing and sampling. The full breakdown of topics is covered session by session in the Course Outline tab above.
The programme is aimed at professionals who detect, investigate or oversee financial crime risk, including: AML and CFT compliance officers, Money laundering reporting officers and their deputies, Financial intelligence unit and law enforcement analysts, Transaction monitoring and sanctions screening analysts, Internal and external auditors reviewing compliance programmes, Fraud and forensic investigators, Risk managers in banks, insurers and mobile money providers, Supervisors and regulators of financial institutions, and Data analysts supporting compliance teams.
Data and Analytics for AML / CFT & Financial Crime Analytics Training Course typically runs as 5 Days. It's available as in-person classroom, live virtual, and in-house corporate training — every course can also be delivered on-site for your team on dates that suit you.
Data and Analytics for AML / CFT & Financial Crime Analytics Training Course is scheduled in-classroom in Nairobi, Kenya, Mombasa, Kenya, Naivasha, Kenya, and Kisumu, Kenya, and 14 other locations, plus a live interactive virtual classroom you can join from anywhere. Check the schedule panel above for exact upcoming dates and fees in each location.
The next live virtual cohort of Data and Analytics for AML / CFT & Financial Crime Analytics starts November 2, 2026, with new classroom cohorts also running on a rolling basis. Pick a date and location in the schedule panel above, then click "Register for the Course" — it takes a few minutes and your seat is confirmed once payment or a signed purchase order is received.
Yes — delegates who meet the attendance requirement receive a Certificate of Completion for Data and Analytics for AML / CFT & Financial Crime Analytics Training Course from Vision Reach Global Consultancy, issued in the name you register with, so double-check the spelling at checkout.
Data and Analytics for AML / CFT & Financial Crime Analytics Training Course is pitched at intermediate professionals. If you're unsure whether it's the right fit for your current role or background, message our training advisors before you register and they'll help you confirm.
Fees for Data and Analytics for AML / CFT & Financial Crime Analytics Training Course vary by delivery location and format and are shown in real time in the schedule panel above once you pick a date. Register 3 or more delegates on the same course together and a 5% team discount is applied automatically — larger cohorts can request a custom corporate quote.
Yes — Data and Analytics for AML / CFT & Financial Crime Analytics Training Course can be delivered on-site at your offices (or virtually for distributed teams), with case studies and examples tailored to your industry and the specific challenges your team is working through. Switch to the "In-House" tab in the schedule panel above to request a proposal.
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